Developability of a drug candidate is decided based on the Pharmacokinetic (PK) and Pharmacodynamic (PD) parameters of the drug candidate, usually estimated using Plasma Concentration Time (PCT) and effect-concentration profiles of the drug candidate, measured in a number of targeted animal/Human in vivo studies. PK is the study of what the body does to a drug, i.e., its absorption, distribution, metabolism and excretion profiles. PK modeling characterizes the blood or plasma concentration-time profiles following administration of a drug via various routes. On the other hand PD defines what a drug does to the body. PD modeling attempts to characterize measured physiological parameters before and after drug administration with the effect defined as the change in parameter relative to pre-dose or baseline value.
The objective of these models is to estimate the PK/PD parameters which is an integral part of model based drug development. The significance of accurately estimating these parameters lies in the fact that many of these parameters cannot be measured experimentally either in human or in animal. Further, the decision to take the compound/drug to the next level of drug development process depends heavily on the accuracy of the parameters values. The accuracy of the optimized parameter estimates obtained using available computing methods such as Gauss-Newton etc, is dependent on appropriate selection of initial parameter values. These estimations may be an educated guess based on the structure of the model, or may be determined by using estimated parameters from previous studies. However, these approaches do not always guarantee good initial estimates of all the PK-PD parameters of interest. Further, the number of parameters and complexity of the model increase the execution time required for a computing method to estimate the parameters.